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Regression trees for hospitality data analysis
International Journal of Contemporary Hospitality Management ( IF 11.1 ) Pub Date : 2023-01-03 , DOI: 10.1108/ijchm-06-2022-0705
Mike Tsionas, A. George Assaf

Purpose

The purpose of this note is to describe the concept of regression trees (RTs) for hospitality data analysis.

Design/methodology/approach

RT is an effective non-parametric predicting modelling approach that would free researchers from the need to force a certain functional form. The method does not require normalization or scaling of data.

Findings

The authors illustrate how RTs can be used to find a model that would result in the best prediction.

Research limitations/implications

A common challenge facing hospitality researchers is to estimate a regression model with the correct specification. RTs can help researchers identify the best explanatory model for prediction.

Originality/value

This paper describes the concept of RTs for the modelling of hospitality data.



中文翻译:

用于酒店数据分析的回归树

目的

本说明的目的是描述用于酒店数据分析的回归树 (RT) 的概念。

设计/方法/途径

RT 是一种有效的非参数预测建模方法,可以使研究人员摆脱强制某种函数形式的需要。该方法不需要对数据进行归一化或缩放。

发现

作者说明了如何使用 RT 来找到能够产生最佳预测的模型。

研究局限性/影响

酒店研究人员面临的一个共同挑战是估计具有正确规范的回归模型。RT 可以帮助研究人员确定最佳的预测解释模型。

原创性/价值

本文描述了用于酒店数据建模的 RT 概念。

更新日期:2023-01-03
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